Is perfect the enemy of good? Weighing the evidence for biparametric MRI in prostate cancer

The role of multiparametric MRI in diagnosis, staging and treatment planning for prostate cancer is well established. However there remain several challenges to widespread adoption. One such challenge is the duration and cost the examination. Abbreviated exams omitting contrast enhanced sequences may help address this challenge. In this review, we will discuss the rationale for biparametric MRI (bpMRI) for detection and characterization of clinically significant prostate cancer prior to biopsy and synthesize the published literature. We will weigh up the advantages and disadvantages to this approach and lay out a conceptual cost/benefit analysis regarding adoption of bpMRI

Network Modeling Sex Differences in Brain Integrity and Metabolic Health

Hypothesis-driven studies have demonstrated that sex moderates many of the relationships between brain health and cardiometabolic disease, which impacts risk for later-life cognitive decline. In the present study, we sought to further our understanding of the associations between multiple markers of brain integrity and cardiovascular risk in a midlife sample of 266 individuals by using network analysis, a technique specifically designed to examine complex associations among multiple systems at once. Separate network models were constructed for male and female participants to investigate sex differences in the biomarkers of interest, selected based on evidence linking them with risk for late-life cognitive decline: all components of metabolic syndrome (obesity, hypertension, dyslipidemia, and hyperglycemia); neuroimaging-derived brain-predicted age minus chronological age; ratio of white matter hyperintensities to whole brain volume; seed-based resting state functional connectivity in the Default Mode Network, and ratios of N-acetyl aspartate, glutamate and myo-inositol to creatine, measured through proton magnetic resonance spectroscopy. Males had a sparse network (87.2% edges = 0) relative to females (69.2% edges = 0), indicating fewer relationships between measures of cardiometabolic risk and brain integrity. The edges in the female network provide meaningful information about potential mechanisms between brain integrity and cardiometabolic health. Additionally, Apolipoprotein ϵ4 (ApoE ϵ4) status and waist circumference emerged as central nodes in the female model. Our study demonstrates that network analysis is a promising technique for examining relationships between risk factors for cognitive decline in a midlife population and that investigating sex differences may help optimize risk prediction and tailor individualized treatments in the future

Envolvimento de "stakeholders" em direcção à construção sustentável

A mudança de paradigma requerida para evoluir na direcção da construção sustentável exige a conjugação efectiva de diferentes condições determinantes, que inclui a percepção, comportamento e envolvimento de partes em todo o processo, em particular os actores que efectam, bem como aqueles que são afectados pela tomada de decisão. Para além das formas convencionais de envolvimento dos stokholders, novas formas de cooperação precisam de ser exploradas. O presente artigo tem por obectivo reflectir sobre a melhor estratégia de gestão a aplicar nos actores-chave num contexto de networking sobre construção sustentável em Portugal. A análise efectuada permitiu verificar que o sucesso de uma plataforma de cooperação está condicionada pela participação dos actores-chave, pelo que há necessidade de fazer o mapeamento, a hierarquização e a definição de uma estratégia de gestão que maximize asua cooperação, isto é, que vá ao encontro das necessidades de cada um deles, para que a plataforma de cooperação se torne um efectivo espaço de partilha, diálogo, aprendizagem e inovação

Deep generative modeling for single-cell transcriptomics.

Single-cell transcriptome measurements can reveal unexplored biological diversity, but they suffer from technical noise and bias that must be modeled to account for the resulting uncertainty in downstream analyses. Here we introduce single-cell variational inference (scVI), a ready-to-use scalable framework for the probabilistic representation and analysis of gene expression in single cells ( https://github.com/YosefLab/scVI ). scVI uses stochastic optimization and deep neural networks to aggregate information across similar cells and genes and to approximate the distributions that underlie observed expression values, while accounting for batch effects and limited sensitivity. We used scVI for a range of fundamental analysis tasks including batch correction, visualization, clustering, and differential expression, and achieved high accuracy for each task

Ambient vibration tests of a cross-laminated timber building

Cross-laminated timber has, in the last 6 years, been used for the first time to form shear walls and cores in multi-storey buildings of seven storeys or more. Such buildings can have low mass in comparison to conventional structural forms. This low mass means that, as cross-laminated timber is used for taller buildings still, their dynamic movement under wind load is likely to be a key design parameter. An understanding of dynamic lateral stiffness and damping, which has so far been insufficiently researched, will be vital to the effective design for wind-induced vibration. In this study, an ambient vibration method is used to identify the dynamic properties of a seven-storey cross-laminated timber building in situ. The random decrement method is used, along with the Ibrahim time domain method, to extract the modal properties of the structure from the acceleration measured under ambient conditions. The results show that this output-only modal analysis method can be used to extract modal information from such a building, and that information is compared with a simple structural model. Measurements on two occasions during construction show the effect of non-structural elements on the modal properties of the structure